Our work adapts this teacher-student setup and shows its benefits beyond image-level tasks.
To this effect, we build on the clustering pretext task from [1]} and reformulate it such that it can be used on an image patch level with teacher-student setups.
We also use the multi-crop augmentation strategy and provide an interpretation from the perspective of dense prediction tasks.
